{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "probtorch: 0.0+5a2c637 torch: 0.4.0 cuda: True\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.nn import Parameter\n",
    "import sys\n",
    "sys.path.append('../')\n",
    "import probtorch\n",
    "from probtorch.util import expand_inputs\n",
    "print('probtorch:', probtorch.__version__, \n",
    "      'torch:', torch.__version__, \n",
    "      'cuda:', torch.cuda.is_available())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model parameters\n",
    "NUM_PIXELS = 784\n",
    "NUM_HIDDEN = 256\n",
    "NUM_DIGITS = 10\n",
    "NUM_LATENT = 10   \n",
    "\n",
    "# training parameters\n",
    "NUM_SAMPLES = 8 \n",
    "NUM_BATCH = 128\n",
    "NUM_EPOCHS = 200\n",
    "LEARNING_RATE = 1e-3\n",
    "BETA1 = 0.90\n",
    "EPS = 1e-9\n",
    "CUDA = torch.cuda.is_available()\n",
    "\n",
    "# path parameters\n",
    "MODEL_NAME = 'mnist-%02ddim' % NUM_LATENT\n",
    "DATA_PATH = '../data'\n",
    "WEIGHTS_PATH = '../weights'\n",
    "RESTORE = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Encoder Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "class Encoder(nn.Module):\n",
    "    def __init__(self, num_pixels=NUM_PIXELS, \n",
    "                       num_hidden=NUM_HIDDEN,\n",
    "                       num_latent=NUM_LATENT,\n",
    "                       num_batch=NUM_BATCH):\n",
    "        super(self.__class__, self).__init__()\n",
    "        self.enc_hidden = nn.Sequential( \n",
    "                            nn.Linear(num_pixels, num_hidden),\n",
    "                            nn.ReLU())\n",
    "        self.z_mean = nn.Linear(num_hidden, num_latent)\n",
    "        self.z_log_std = nn.Linear(num_hidden, num_latent)\n",
    "    \n",
    "    @expand_inputs\n",
    "    def forward(self, images, labels=None, num_samples=None):\n",
    "        q = probtorch.Trace()\n",
    "        hiddens = self.enc_hidden(images)\n",
    "        q.normal(self.z_mean(hiddens),\n",
    "                 self.z_log_std(hiddens).exp(),\n",
    "                 name='z')\n",
    "        return q"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decoder Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Decoder(nn.Module):\n",
    "    def __init__(self, num_pixels=NUM_PIXELS, \n",
    "                       num_hidden=NUM_HIDDEN,\n",
    "                       num_latent=NUM_LATENT):\n",
    "        super(self.__class__, self).__init__()\n",
    "        self.z_mean = torch.zeros(num_latent)\n",
    "        self.z_std = torch.ones(num_latent)\n",
    "        self.dec_image = nn.Sequential(\n",
    "                           nn.Linear(num_latent, num_hidden),\n",
    "                           nn.ReLU(),\n",
    "                           nn.Linear(num_hidden, num_pixels),\n",
    "                           nn.Sigmoid())\n",
    "\n",
    "    def forward(self, images, q=None, num_samples=None):\n",
    "        p = probtorch.Trace()\n",
    "        z = p.normal(self.z_mean, \n",
    "                     self.z_std,\n",
    "                     value=q['z'],\n",
    "                     name='z')\n",
    "        images_mean = self.dec_image(z)\n",
    "        p.loss(lambda x_hat, x: -(torch.log(x_hat + EPS) * x + \n",
    "                                  torch.log(1 - x_hat + EPS) * (1-x)).sum(-1),\n",
    "               images_mean, images, name='x')\n",
    "        return p"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def elbo(q, p, alpha=0.1):\n",
    "    if NUM_SAMPLES is None:\n",
    "        return probtorch.objectives.montecarlo.elbo(q, p, sample_dim=None, batch_dim=0, alpha=alpha)\n",
    "    else:\n",
    "        return probtorch.objectives.montecarlo.elbo(q, p, sample_dim=0, batch_dim=1, alpha=alpha)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision import datasets, transforms\n",
    "import os \n",
    "\n",
    "if not os.path.isdir(DATA_PATH):\n",
    "    os.makedirs(DATA_PATH)\n",
    "\n",
    "train_data = torch.utils.data.DataLoader(\n",
    "                datasets.MNIST(DATA_PATH, train=True, download=True,\n",
    "                               transform=transforms.ToTensor()),\n",
    "                batch_size=NUM_BATCH, shuffle=True) \n",
    "test_data = torch.utils.data.DataLoader(\n",
    "                datasets.MNIST(DATA_PATH, train=False, download=True,\n",
    "                               transform=transforms.ToTensor()),\n",
    "                batch_size=NUM_BATCH, shuffle=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training and Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cuda_tensors(obj): \n",
    "    for attr in dir(obj):\n",
    "        value = getattr(obj, attr)\n",
    "        if isinstance(value, torch.Tensor):\n",
    "            setattr(obj, attr, value.cuda())\n",
    "\n",
    "enc = Encoder()\n",
    "dec = Decoder()\n",
    "if CUDA:\n",
    "    enc.cuda()\n",
    "    dec.cuda()\n",
    "    cuda_tensors(enc)\n",
    "    cuda_tensors(dec)\n",
    "\n",
    "optimizer =  torch.optim.Adam(list(enc.parameters())+list(dec.parameters()),\n",
    "                              lr=LEARNING_RATE,\n",
    "                              betas=(BETA1, 0.999))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(data, enc, dec, optimizer):\n",
    "    epoch_elbo = 0.0\n",
    "    enc.train()\n",
    "    dec.train()\n",
    "    N = 0\n",
    "    for b, (images, labels) in enumerate(data):\n",
    "        if images.size()[0] == NUM_BATCH:\n",
    "            N += NUM_BATCH\n",
    "            images = images.view(-1, NUM_PIXELS)\n",
    "            if CUDA:\n",
    "                images = images.cuda()\n",
    "            optimizer.zero_grad()\n",
    "            q = enc(images, num_samples=NUM_SAMPLES)\n",
    "            p = dec(images, q, num_samples=NUM_SAMPLES)\n",
    "            loss = -elbo(q, p)\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "            if CUDA:\n",
    "                loss = loss.cpu()\n",
    "            epoch_elbo -= float(loss.item())\n",
    "    return epoch_elbo / N\n",
    "\n",
    "def test(data, enc, dec):\n",
    "    enc.eval()\n",
    "    dec.eval()\n",
    "    epoch_elbo = 0.0\n",
    "    N = 0\n",
    "    for b, (images, labels) in enumerate(data):\n",
    "        if images.size()[0] == NUM_BATCH:\n",
    "            N += NUM_BATCH\n",
    "            images = images.view(-1, NUM_PIXELS)\n",
    "            if CUDA:\n",
    "                images = images.cuda()\n",
    "            q = enc(images, num_samples=NUM_SAMPLES)\n",
    "            p = dec(images, q, num_samples=NUM_SAMPLES)\n",
    "            batch_elbo = elbo(q, p)\n",
    "            if CUDA:\n",
    "                batch_elbo = batch_elbo.cpu()\n",
    "            epoch_elbo += float(batch_elbo.item())\n",
    "    return epoch_elbo / N"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 0] Train: ELBO -1.3498e+00 (3s) Test: ELBO -1.0316e+00 (0s)\n",
      "[Epoch 1] Train: ELBO -9.9317e-01 (3s) Test: ELBO -9.5292e-01 (0s)\n",
      "[Epoch 2] Train: ELBO -9.4539e-01 (3s) Test: ELBO -9.2314e-01 (0s)\n",
      "[Epoch 3] Train: ELBO -9.2279e-01 (3s) Test: ELBO -9.0601e-01 (0s)\n",
      "[Epoch 4] Train: ELBO -9.0854e-01 (3s) Test: ELBO -8.9529e-01 (0s)\n",
      "[Epoch 5] Train: ELBO -8.9850e-01 (3s) Test: ELBO -8.8825e-01 (0s)\n",
      "[Epoch 6] Train: ELBO -8.9066e-01 (3s) Test: ELBO -8.8083e-01 (0s)\n",
      "[Epoch 7] Train: ELBO -8.8449e-01 (3s) Test: ELBO -8.7669e-01 (0s)\n",
      "[Epoch 8] Train: ELBO -8.7961e-01 (3s) Test: ELBO -8.7176e-01 (0s)\n",
      "[Epoch 9] Train: ELBO -8.7532e-01 (3s) Test: ELBO -8.6877e-01 (0s)\n",
      "[Epoch 10] Train: ELBO -8.7151e-01 (3s) Test: ELBO -8.6501e-01 (0s)\n",
      "[Epoch 11] Train: ELBO -8.6828e-01 (3s) Test: ELBO -8.6336e-01 (0s)\n",
      "[Epoch 12] Train: ELBO -8.6552e-01 (3s) Test: ELBO -8.6143e-01 (0s)\n",
      "[Epoch 13] Train: ELBO -8.6301e-01 (3s) Test: ELBO -8.5844e-01 (0s)\n",
      "[Epoch 14] Train: ELBO -8.6053e-01 (3s) Test: ELBO -8.5569e-01 (0s)\n",
      "[Epoch 15] Train: ELBO -8.5840e-01 (3s) Test: ELBO -8.5522e-01 (0s)\n",
      "[Epoch 16] Train: ELBO -8.5642e-01 (3s) Test: ELBO -8.5485e-01 (0s)\n",
      "[Epoch 17] Train: ELBO -8.5443e-01 (3s) Test: ELBO -8.5162e-01 (0s)\n",
      "[Epoch 18] Train: ELBO -8.5267e-01 (3s) Test: ELBO -8.5080e-01 (0s)\n",
      "[Epoch 19] Train: ELBO -8.5114e-01 (3s) Test: ELBO -8.4783e-01 (0s)\n",
      "[Epoch 20] Train: ELBO -8.4980e-01 (3s) Test: ELBO -8.4729e-01 (0s)\n",
      "[Epoch 21] Train: ELBO -8.4830e-01 (3s) Test: ELBO -8.4684e-01 (0s)\n",
      "[Epoch 22] Train: ELBO -8.4709e-01 (3s) Test: ELBO -8.4656e-01 (0s)\n",
      "[Epoch 23] Train: ELBO -8.4596e-01 (3s) Test: ELBO -8.4628e-01 (0s)\n",
      "[Epoch 24] Train: ELBO -8.4457e-01 (3s) Test: ELBO -8.4417e-01 (0s)\n",
      "[Epoch 25] Train: ELBO -8.4359e-01 (3s) Test: ELBO -8.4283e-01 (0s)\n",
      "[Epoch 26] Train: ELBO -8.4250e-01 (3s) Test: ELBO -8.4293e-01 (0s)\n",
      "[Epoch 27] Train: ELBO -8.4155e-01 (3s) Test: ELBO -8.4249e-01 (0s)\n",
      "[Epoch 28] Train: ELBO -8.4075e-01 (3s) Test: ELBO -8.4021e-01 (0s)\n",
      "[Epoch 29] Train: ELBO -8.3975e-01 (3s) Test: ELBO -8.3942e-01 (0s)\n",
      "[Epoch 30] Train: ELBO -8.3897e-01 (3s) Test: ELBO -8.3927e-01 (0s)\n",
      "[Epoch 31] Train: ELBO -8.3833e-01 (3s) Test: ELBO -8.3870e-01 (0s)\n",
      "[Epoch 32] Train: ELBO -8.3745e-01 (3s) Test: ELBO -8.3880e-01 (0s)\n",
      "[Epoch 33] Train: ELBO -8.3670e-01 (3s) Test: ELBO -8.3772e-01 (0s)\n",
      "[Epoch 34] Train: ELBO -8.3606e-01 (3s) Test: ELBO -8.3774e-01 (0s)\n",
      "[Epoch 35] Train: ELBO -8.3538e-01 (3s) Test: ELBO -8.3790e-01 (0s)\n",
      "[Epoch 36] Train: ELBO -8.3482e-01 (3s) Test: ELBO -8.3607e-01 (0s)\n",
      "[Epoch 37] Train: ELBO -8.3432e-01 (3s) Test: ELBO -8.3617e-01 (0s)\n",
      "[Epoch 38] Train: ELBO -8.3353e-01 (3s) Test: ELBO -8.3616e-01 (0s)\n",
      "[Epoch 39] Train: ELBO -8.3301e-01 (3s) Test: ELBO -8.3667e-01 (0s)\n",
      "[Epoch 40] Train: ELBO -8.3271e-01 (3s) Test: ELBO -8.3527e-01 (0s)\n",
      "[Epoch 41] Train: ELBO -8.3201e-01 (3s) Test: ELBO -8.3572e-01 (0s)\n",
      "[Epoch 42] Train: ELBO -8.3161e-01 (3s) Test: ELBO -8.3438e-01 (0s)\n",
      "[Epoch 43] Train: ELBO -8.3110e-01 (3s) Test: ELBO -8.3523e-01 (0s)\n",
      "[Epoch 44] Train: ELBO -8.3070e-01 (3s) Test: ELBO -8.3332e-01 (0s)\n",
      "[Epoch 45] Train: ELBO -8.3010e-01 (3s) Test: ELBO -8.3352e-01 (0s)\n",
      "[Epoch 46] Train: ELBO -8.2970e-01 (3s) Test: ELBO -8.3362e-01 (0s)\n",
      "[Epoch 47] Train: ELBO -8.2931e-01 (3s) Test: ELBO -8.3295e-01 (0s)\n",
      "[Epoch 48] Train: ELBO -8.2903e-01 (3s) Test: ELBO -8.3261e-01 (0s)\n",
      "[Epoch 49] Train: ELBO -8.2860e-01 (3s) Test: ELBO -8.3203e-01 (0s)\n",
      "[Epoch 50] Train: ELBO -8.2829e-01 (3s) Test: ELBO -8.3163e-01 (0s)\n",
      "[Epoch 51] Train: ELBO -8.2780e-01 (3s) Test: ELBO -8.3193e-01 (0s)\n",
      "[Epoch 52] Train: ELBO -8.2747e-01 (3s) Test: ELBO -8.3195e-01 (0s)\n",
      "[Epoch 53] Train: ELBO -8.2716e-01 (3s) Test: ELBO -8.3177e-01 (0s)\n",
      "[Epoch 54] Train: ELBO -8.2697e-01 (3s) Test: ELBO -8.3132e-01 (0s)\n",
      "[Epoch 55] Train: ELBO -8.2648e-01 (3s) Test: ELBO -8.3054e-01 (0s)\n",
      "[Epoch 56] Train: ELBO -8.2621e-01 (3s) Test: ELBO -8.3062e-01 (0s)\n",
      "[Epoch 57] Train: ELBO -8.2607e-01 (3s) Test: ELBO -8.3077e-01 (0s)\n",
      "[Epoch 58] Train: ELBO -8.2553e-01 (3s) Test: ELBO -8.3038e-01 (0s)\n",
      "[Epoch 59] Train: ELBO -8.2540e-01 (3s) Test: ELBO -8.2994e-01 (0s)\n",
      "[Epoch 60] Train: ELBO -8.2506e-01 (3s) Test: ELBO -8.3092e-01 (0s)\n",
      "[Epoch 61] Train: ELBO -8.2494e-01 (3s) Test: ELBO -8.3042e-01 (0s)\n",
      "[Epoch 62] Train: ELBO -8.2456e-01 (3s) Test: ELBO -8.2900e-01 (0s)\n",
      "[Epoch 63] Train: ELBO -8.2425e-01 (3s) Test: ELBO -8.3012e-01 (0s)\n",
      "[Epoch 64] Train: ELBO -8.2409e-01 (3s) Test: ELBO -8.2943e-01 (0s)\n",
      "[Epoch 65] Train: ELBO -8.2383e-01 (3s) Test: ELBO -8.2876e-01 (0s)\n",
      "[Epoch 66] Train: ELBO -8.2372e-01 (3s) Test: ELBO -8.2979e-01 (0s)\n",
      "[Epoch 67] Train: ELBO -8.2330e-01 (3s) Test: ELBO -8.2789e-01 (0s)\n",
      "[Epoch 68] Train: ELBO -8.2315e-01 (3s) Test: ELBO -8.2887e-01 (0s)\n",
      "[Epoch 69] Train: ELBO -8.2286e-01 (3s) Test: ELBO -8.2894e-01 (0s)\n",
      "[Epoch 70] Train: ELBO -8.2249e-01 (3s) Test: ELBO -8.2856e-01 (0s)\n",
      "[Epoch 71] Train: ELBO -8.2239e-01 (3s) Test: ELBO -8.2862e-01 (0s)\n",
      "[Epoch 72] Train: ELBO -8.2232e-01 (3s) Test: ELBO -8.2807e-01 (0s)\n",
      "[Epoch 73] Train: ELBO -8.2190e-01 (3s) Test: ELBO -8.2791e-01 (0s)\n",
      "[Epoch 74] Train: ELBO -8.2174e-01 (3s) Test: ELBO -8.2769e-01 (0s)\n",
      "[Epoch 75] Train: ELBO -8.2159e-01 (3s) Test: ELBO -8.2807e-01 (0s)\n",
      "[Epoch 76] Train: ELBO -8.2147e-01 (3s) Test: ELBO -8.2761e-01 (0s)\n",
      "[Epoch 77] Train: ELBO -8.2119e-01 (3s) Test: ELBO -8.2798e-01 (0s)\n",
      "[Epoch 78] Train: ELBO -8.2111e-01 (3s) Test: ELBO -8.2713e-01 (0s)\n",
      "[Epoch 79] Train: ELBO -8.2074e-01 (3s) Test: ELBO -8.2749e-01 (0s)\n",
      "[Epoch 80] Train: ELBO -8.2069e-01 (3s) Test: ELBO -8.2689e-01 (0s)\n",
      "[Epoch 81] Train: ELBO -8.2030e-01 (3s) Test: ELBO -8.2758e-01 (0s)\n",
      "[Epoch 82] Train: ELBO -8.2014e-01 (3s) Test: ELBO -8.2792e-01 (0s)\n",
      "[Epoch 83] Train: ELBO -8.2008e-01 (3s) Test: ELBO -8.2727e-01 (0s)\n",
      "[Epoch 84] Train: ELBO -8.1982e-01 (3s) Test: ELBO -8.2778e-01 (0s)\n",
      "[Epoch 85] Train: ELBO -8.1977e-01 (3s) Test: ELBO -8.2771e-01 (0s)\n",
      "[Epoch 86] Train: ELBO -8.1951e-01 (3s) Test: ELBO -8.2641e-01 (0s)\n",
      "[Epoch 87] Train: ELBO -8.1950e-01 (3s) Test: ELBO -8.2691e-01 (0s)\n",
      "[Epoch 88] Train: ELBO -8.1924e-01 (3s) Test: ELBO -8.2657e-01 (0s)\n",
      "[Epoch 89] Train: ELBO -8.1907e-01 (3s) Test: ELBO -8.2621e-01 (0s)\n",
      "[Epoch 90] Train: ELBO -8.1897e-01 (3s) Test: ELBO -8.2614e-01 (0s)\n",
      "[Epoch 91] Train: ELBO -8.1874e-01 (3s) Test: ELBO -8.2649e-01 (0s)\n",
      "[Epoch 92] Train: ELBO -8.1858e-01 (3s) Test: ELBO -8.2634e-01 (0s)\n",
      "[Epoch 93] Train: ELBO -8.1856e-01 (3s) Test: ELBO -8.2688e-01 (0s)\n",
      "[Epoch 94] Train: ELBO -8.1830e-01 (3s) Test: ELBO -8.2602e-01 (0s)\n",
      "[Epoch 95] Train: ELBO -8.1827e-01 (3s) Test: ELBO -8.2603e-01 (0s)\n",
      "[Epoch 96] Train: ELBO -8.1813e-01 (3s) Test: ELBO -8.2736e-01 (0s)\n",
      "[Epoch 97] Train: ELBO -8.1783e-01 (3s) Test: ELBO -8.2690e-01 (0s)\n",
      "[Epoch 98] Train: ELBO -8.1779e-01 (3s) Test: ELBO -8.2613e-01 (0s)\n",
      "[Epoch 99] Train: ELBO -8.1760e-01 (3s) Test: ELBO -8.2547e-01 (0s)\n",
      "[Epoch 100] Train: ELBO -8.1748e-01 (3s) Test: ELBO -8.2568e-01 (0s)\n",
      "[Epoch 101] Train: ELBO -8.1753e-01 (3s) Test: ELBO -8.2555e-01 (0s)\n",
      "[Epoch 102] Train: ELBO -8.1726e-01 (3s) Test: ELBO -8.2550e-01 (0s)\n",
      "[Epoch 103] Train: ELBO -8.1724e-01 (3s) Test: ELBO -8.2489e-01 (0s)\n",
      "[Epoch 104] Train: ELBO -8.1703e-01 (3s) Test: ELBO -8.2599e-01 (0s)\n",
      "[Epoch 105] Train: ELBO -8.1681e-01 (3s) Test: ELBO -8.2474e-01 (0s)\n",
      "[Epoch 106] Train: ELBO -8.1667e-01 (3s) Test: ELBO -8.2524e-01 (0s)\n",
      "[Epoch 107] Train: ELBO -8.1650e-01 (3s) Test: ELBO -8.2495e-01 (0s)\n",
      "[Epoch 108] Train: ELBO -8.1653e-01 (3s) Test: ELBO -8.2471e-01 (0s)\n",
      "[Epoch 109] Train: ELBO -8.1633e-01 (3s) Test: ELBO -8.2494e-01 (0s)\n",
      "[Epoch 110] Train: ELBO -8.1630e-01 (3s) Test: ELBO -8.2531e-01 (0s)\n",
      "[Epoch 111] Train: ELBO -8.1613e-01 (3s) Test: ELBO -8.2530e-01 (0s)\n",
      "[Epoch 112] Train: ELBO -8.1608e-01 (3s) Test: ELBO -8.2482e-01 (0s)\n",
      "[Epoch 113] Train: ELBO -8.1591e-01 (3s) Test: ELBO -8.2456e-01 (0s)\n",
      "[Epoch 114] Train: ELBO -8.1580e-01 (3s) Test: ELBO -8.2511e-01 (0s)\n",
      "[Epoch 115] Train: ELBO -8.1559e-01 (3s) Test: ELBO -8.2466e-01 (0s)\n",
      "[Epoch 116] Train: ELBO -8.1561e-01 (3s) Test: ELBO -8.2542e-01 (0s)\n",
      "[Epoch 117] Train: ELBO -8.1549e-01 (3s) Test: ELBO -8.2451e-01 (0s)\n",
      "[Epoch 118] Train: ELBO -8.1552e-01 (3s) Test: ELBO -8.2441e-01 (0s)\n",
      "[Epoch 119] Train: ELBO -8.1518e-01 (3s) Test: ELBO -8.2510e-01 (0s)\n",
      "[Epoch 120] Train: ELBO -8.1513e-01 (3s) Test: ELBO -8.2459e-01 (0s)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 121] Train: ELBO -8.1505e-01 (3s) Test: ELBO -8.2455e-01 (0s)\n",
      "[Epoch 122] Train: ELBO -8.1490e-01 (3s) Test: ELBO -8.2411e-01 (0s)\n",
      "[Epoch 123] Train: ELBO -8.1498e-01 (3s) Test: ELBO -8.2437e-01 (0s)\n",
      "[Epoch 124] Train: ELBO -8.1488e-01 (3s) Test: ELBO -8.2340e-01 (0s)\n",
      "[Epoch 125] Train: ELBO -8.1470e-01 (3s) Test: ELBO -8.2439e-01 (0s)\n",
      "[Epoch 126] Train: ELBO -8.1484e-01 (3s) Test: ELBO -8.2379e-01 (0s)\n",
      "[Epoch 127] Train: ELBO -8.1434e-01 (3s) Test: ELBO -8.2422e-01 (0s)\n",
      "[Epoch 128] Train: ELBO -8.1434e-01 (3s) Test: ELBO -8.2346e-01 (0s)\n",
      "[Epoch 129] Train: ELBO -8.1419e-01 (3s) Test: ELBO -8.2390e-01 (0s)\n",
      "[Epoch 130] Train: ELBO -8.1424e-01 (3s) Test: ELBO -8.2425e-01 (0s)\n",
      "[Epoch 131] Train: ELBO -8.1417e-01 (3s) Test: ELBO -8.2414e-01 (0s)\n",
      "[Epoch 132] Train: ELBO -8.1400e-01 (3s) Test: ELBO -8.2422e-01 (0s)\n",
      "[Epoch 133] Train: ELBO -8.1396e-01 (3s) Test: ELBO -8.2318e-01 (0s)\n",
      "[Epoch 134] Train: ELBO -8.1379e-01 (3s) Test: ELBO -8.2339e-01 (0s)\n",
      "[Epoch 135] Train: ELBO -8.1387e-01 (3s) Test: ELBO -8.2418e-01 (0s)\n",
      "[Epoch 136] Train: ELBO -8.1375e-01 (3s) Test: ELBO -8.2390e-01 (0s)\n",
      "[Epoch 137] Train: ELBO -8.1364e-01 (3s) Test: ELBO -8.2445e-01 (0s)\n",
      "[Epoch 138] Train: ELBO -8.1360e-01 (3s) Test: ELBO -8.2295e-01 (0s)\n",
      "[Epoch 139] Train: ELBO -8.1325e-01 (3s) Test: ELBO -8.2359e-01 (0s)\n",
      "[Epoch 140] Train: ELBO -8.1344e-01 (3s) Test: ELBO -8.2350e-01 (0s)\n",
      "[Epoch 141] Train: ELBO -8.1321e-01 (3s) Test: ELBO -8.2281e-01 (0s)\n",
      "[Epoch 142] Train: ELBO -8.1307e-01 (3s) Test: ELBO -8.2415e-01 (0s)\n",
      "[Epoch 143] Train: ELBO -8.1301e-01 (3s) Test: ELBO -8.2323e-01 (0s)\n",
      "[Epoch 144] Train: ELBO -8.1314e-01 (3s) Test: ELBO -8.2347e-01 (0s)\n",
      "[Epoch 145] Train: ELBO -8.1294e-01 (3s) Test: ELBO -8.2334e-01 (0s)\n",
      "[Epoch 146] Train: ELBO -8.1282e-01 (3s) Test: ELBO -8.2361e-01 (0s)\n",
      "[Epoch 147] Train: ELBO -8.1277e-01 (3s) Test: ELBO -8.2326e-01 (0s)\n",
      "[Epoch 148] Train: ELBO -8.1278e-01 (3s) Test: ELBO -8.2366e-01 (0s)\n",
      "[Epoch 149] Train: ELBO -8.1276e-01 (3s) Test: ELBO -8.2304e-01 (0s)\n",
      "[Epoch 150] Train: ELBO -8.1270e-01 (3s) Test: ELBO -8.2337e-01 (0s)\n",
      "[Epoch 151] Train: ELBO -8.1253e-01 (3s) Test: ELBO -8.2258e-01 (0s)\n",
      "[Epoch 152] Train: ELBO -8.1237e-01 (3s) Test: ELBO -8.2361e-01 (0s)\n",
      "[Epoch 153] Train: ELBO -8.1232e-01 (3s) Test: ELBO -8.2274e-01 (0s)\n",
      "[Epoch 154] Train: ELBO -8.1246e-01 (3s) Test: ELBO -8.2327e-01 (0s)\n",
      "[Epoch 155] Train: ELBO -8.1224e-01 (3s) Test: ELBO -8.2328e-01 (0s)\n",
      "[Epoch 156] Train: ELBO -8.1222e-01 (3s) Test: ELBO -8.2244e-01 (0s)\n",
      "[Epoch 157] Train: ELBO -8.1213e-01 (3s) Test: ELBO -8.2346e-01 (0s)\n",
      "[Epoch 158] Train: ELBO -8.1202e-01 (3s) Test: ELBO -8.2353e-01 (0s)\n",
      "[Epoch 159] Train: ELBO -8.1191e-01 (3s) Test: ELBO -8.2356e-01 (0s)\n",
      "[Epoch 160] Train: ELBO -8.1185e-01 (3s) Test: ELBO -8.2336e-01 (0s)\n",
      "[Epoch 161] Train: ELBO -8.1177e-01 (3s) Test: ELBO -8.2332e-01 (0s)\n",
      "[Epoch 162] Train: ELBO -8.1186e-01 (3s) Test: ELBO -8.2287e-01 (0s)\n",
      "[Epoch 163] Train: ELBO -8.1175e-01 (3s) Test: ELBO -8.2256e-01 (0s)\n",
      "[Epoch 164] Train: ELBO -8.1171e-01 (3s) Test: ELBO -8.2287e-01 (0s)\n",
      "[Epoch 165] Train: ELBO -8.1162e-01 (3s) Test: ELBO -8.2239e-01 (0s)\n",
      "[Epoch 166] Train: ELBO -8.1138e-01 (3s) Test: ELBO -8.2262e-01 (0s)\n",
      "[Epoch 167] Train: ELBO -8.1152e-01 (3s) Test: ELBO -8.2292e-01 (0s)\n",
      "[Epoch 168] Train: ELBO -8.1127e-01 (3s) Test: ELBO -8.2338e-01 (0s)\n",
      "[Epoch 169] Train: ELBO -8.1141e-01 (3s) Test: ELBO -8.2286e-01 (0s)\n",
      "[Epoch 170] Train: ELBO -8.1142e-01 (3s) Test: ELBO -8.2299e-01 (0s)\n",
      "[Epoch 171] Train: ELBO -8.1103e-01 (3s) Test: ELBO -8.2326e-01 (0s)\n",
      "[Epoch 172] Train: ELBO -8.1129e-01 (3s) Test: ELBO -8.2296e-01 (0s)\n",
      "[Epoch 173] Train: ELBO -8.1116e-01 (3s) Test: ELBO -8.2219e-01 (0s)\n",
      "[Epoch 174] Train: ELBO -8.1096e-01 (3s) Test: ELBO -8.2234e-01 (0s)\n",
      "[Epoch 175] Train: ELBO -8.1090e-01 (3s) Test: ELBO -8.2331e-01 (0s)\n",
      "[Epoch 176] Train: ELBO -8.1095e-01 (3s) Test: ELBO -8.2275e-01 (0s)\n",
      "[Epoch 177] Train: ELBO -8.1078e-01 (3s) Test: ELBO -8.2241e-01 (0s)\n",
      "[Epoch 178] Train: ELBO -8.1081e-01 (3s) Test: ELBO -8.2281e-01 (0s)\n",
      "[Epoch 179] Train: ELBO -8.1065e-01 (3s) Test: ELBO -8.2259e-01 (0s)\n",
      "[Epoch 180] Train: ELBO -8.1080e-01 (3s) Test: ELBO -8.2166e-01 (0s)\n",
      "[Epoch 181] Train: ELBO -8.1064e-01 (3s) Test: ELBO -8.2247e-01 (0s)\n",
      "[Epoch 182] Train: ELBO -8.1072e-01 (3s) Test: ELBO -8.2282e-01 (0s)\n",
      "[Epoch 183] Train: ELBO -8.1060e-01 (3s) Test: ELBO -8.2186e-01 (0s)\n",
      "[Epoch 184] Train: ELBO -8.1044e-01 (3s) Test: ELBO -8.2349e-01 (0s)\n",
      "[Epoch 185] Train: ELBO -8.1056e-01 (3s) Test: ELBO -8.2289e-01 (0s)\n",
      "[Epoch 186] Train: ELBO -8.1041e-01 (3s) Test: ELBO -8.2237e-01 (0s)\n",
      "[Epoch 187] Train: ELBO -8.1017e-01 (3s) Test: ELBO -8.2247e-01 (0s)\n",
      "[Epoch 188] Train: ELBO -8.1022e-01 (3s) Test: ELBO -8.2197e-01 (0s)\n",
      "[Epoch 189] Train: ELBO -8.1004e-01 (3s) Test: ELBO -8.2213e-01 (0s)\n",
      "[Epoch 190] Train: ELBO -8.0998e-01 (3s) Test: ELBO -8.2192e-01 (0s)\n",
      "[Epoch 191] Train: ELBO -8.1002e-01 (3s) Test: ELBO -8.2224e-01 (0s)\n",
      "[Epoch 192] Train: ELBO -8.1005e-01 (3s) Test: ELBO -8.2251e-01 (0s)\n",
      "[Epoch 193] Train: ELBO -8.1013e-01 (3s) Test: ELBO -8.2236e-01 (0s)\n",
      "[Epoch 194] Train: ELBO -8.0983e-01 (3s) Test: ELBO -8.2232e-01 (0s)\n",
      "[Epoch 195] Train: ELBO -8.0997e-01 (3s) Test: ELBO -8.2266e-01 (0s)\n",
      "[Epoch 196] Train: ELBO -8.0978e-01 (3s) Test: ELBO -8.2172e-01 (0s)\n",
      "[Epoch 197] Train: ELBO -8.0962e-01 (3s) Test: ELBO -8.2230e-01 (0s)\n",
      "[Epoch 198] Train: ELBO -8.0974e-01 (3s) Test: ELBO -8.2205e-01 (0s)\n",
      "[Epoch 199] Train: ELBO -8.0973e-01 (3s) Test: ELBO -8.2227e-01 (0s)\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "from random import random\n",
    "if not RESTORE:\n",
    "    mask = {}\n",
    "    for e in range(NUM_EPOCHS):\n",
    "        train_start = time.time()\n",
    "        train_elbo = train(train_data, enc, dec, optimizer)\n",
    "        train_end = time.time()\n",
    "        test_start = time.time()\n",
    "        test_elbo = test(test_data, enc, dec)\n",
    "        test_end = time.time()\n",
    "        print('[Epoch %d] Train: ELBO %.4e (%ds) Test: ELBO %.4e (%ds)' % (\n",
    "                e, train_elbo, train_end - train_start, \n",
    "                test_elbo, test_end - test_start))\n",
    "\n",
    "    if not os.path.isdir(WEIGHTS_PATH):\n",
    "        os.mkdir(WEIGHTS_PATH)\n",
    "    torch.save(enc.state_dict(),\n",
    "               '%s/%s-%s-%s-enc.rar' % (WEIGHTS_PATH, MODEL_NAME, probtorch.__version__, torch.__version__))\n",
    "    torch.save(dec.state_dict(),\n",
    "               '%s/%s-%s-%s-dec.rar' % (WEIGHTS_PATH, MODEL_NAME, probtorch.__version__, torch.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "if RESTORE:\n",
    "    enc.load_state_dict(torch.load('%s/%s-%s-%s-enc.rar' % (WEIGHTS_PATH, MODEL_NAME, probtorch.__version__, torch.__version__)))\n",
    "    dec.load_state_dict(torch.load('%s/%s-%s-%s-dec.rar' % (WEIGHTS_PATH, MODEL_NAME, probtorch.__version__, torch.__version__)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize Embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "ys = []\n",
    "zs = []\n",
    "for (x, y) in test_data:\n",
    "    if len(x) == NUM_BATCH:\n",
    "        images = x.view(-1, NUM_PIXELS)\n",
    "        if CUDA:\n",
    "            q = enc(images.cuda())\n",
    "            z = q['z'].value.cpu().detach().numpy()\n",
    "        else:\n",
    "            q = enc(images)\n",
    "            z = q['z'].value.data.detach().numpy()\n",
    "        zs.append(z)\n",
    "        ys.append(y.numpy())\n",
    "ys = np.concatenate(ys,0)\n",
    "zs = np.concatenate(zs,0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run TSNE when number of latent dims exceeds 2\n",
    "if NUM_LATENT > 2:\n",
    "    from sklearn.manifold import TSNE\n",
    "    zs2 = TSNE().fit_transform(zs)\n",
    "    zs2_mean = zs2.mean(0)\n",
    "    zs2_std = zs2.std(0)\n",
    "else:\n",
    "    zs2 = zs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# display a 2D plot of the digit classes in the latent space\n",
    "fig = plt.figure(figsize=(6,6))\n",
    "ax = plt.gca()\n",
    "\n",
    "colors = []\n",
    "for k in range(10):\n",
    "    m = (ys == k)\n",
    "    p = ax.scatter(zs2[m, 0], zs2[m, 1], label='y=%d' % k, alpha=0.5, s=5)\n",
    "    colors.append(p.get_facecolor())\n",
    "ax.legend()\n",
    "\n",
    "fig.tight_layout()\n",
    "#fig.savefig('images/%s-%02d-encodings.png' % (MODEL_NAME, NUM_STYLE), dpi=300)\n",
    "\n",
    "x_lim = ax.get_xlim()\n",
    "y_lim = ax.get_ylim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x306 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# display a 2D plot of the digit classes in the latent space\n",
    "fig = plt.figure(figsize=(10,4.25))\n",
    "\n",
    "for k in range(10):\n",
    "    ax = plt.subplot(2,5,k+1)\n",
    "    m = (ys == k)\n",
    "    ax.scatter(zs2[m, 0], zs2[m, 1], alpha=0.5, s=5, c=colors[k])\n",
    "    ax.set_xlim(x_lim)\n",
    "    ax.set_ylim(y_lim)\n",
    "    ax.set_title('y=%d' % k)\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize Reconstructed Digits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x378 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x,_ = next(iter(train_data))\n",
    "x_var = x.view(-1, NUM_PIXELS)\n",
    "if CUDA:\n",
    "    q = enc(x_var.cuda())\n",
    "    p = dec(x_var.cuda(), q)\n",
    "    x_mean = p['x'].value.view(NUM_BATCH, 28, 28).data.cpu().numpy()\n",
    "else:\n",
    "    q = enc(x_var)\n",
    "    p = dec(x_var, q)\n",
    "    x_mean = p['x'].value.view(NUM_BATCH, 28, 28).data.numpy().squeeze()\n",
    "    \n",
    "fig = plt.figure(figsize=(12,5.25))\n",
    "for k in range(5):\n",
    "    ax = plt.subplot(2, 5, k+1)\n",
    "    ax.imshow(x[k].squeeze())\n",
    "    #ax.set_title(\"original\")\n",
    "    plt.axis(\"off\")\n",
    "    ax = plt.subplot(2, 5, k+6)\n",
    "    ax.imshow(x_mean[k].squeeze())\n",
    "    #ax.set_title(\"reconstructed\")\n",
    "    plt.axis(\"off\")\n",
    "    \n",
    "fig.tight_layout()\n",
    "#fig.savefig('images/%s-%02d-reconstructions-separate.png' % (MODEL_NAME, NUM_STYLE), dpi=300, facecolor=[0,0,0,0])"
   ]
  }
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